Biocompatibility and feasibility of VisiPlate, a novel ultrathin, multichannel glaucoma drainage device
Bibliographic record
Abstract
BACKGROUND: Glaucoma is the leading cause of blindness worldwide. Glaucoma drainage devices and minimally invasive glaucoma surgeries (MIGS) often present with tradeoffs in safety and durability of efficacy. Using a rabbit model, we examined the biocompatibility and feasibility of VisiPlate, a novel, ultrathin, tubeless subconjunctival shunt comprised of a network of microchannels. METHODS: Six naive female New Zealand White rabbits received implants (three only in the right eye with contralateral eye untreated and three in both eyes) composed of a 400-nm-thick aluminum oxide core coated with 2 µm of parylene-C, manufactured with microelectromechanical systems (MEMS) techniques. Tonometry, slit lamp exam, clinical exam, fluorescein patency testing, and histopathology were performed. RESULTS: VisiPlate demonstrated IOP-lowering of 20-40% compared to baseline at each time point over the course of 3 months in the nine implanted eyes. All eyes developed blebs over the implant, and fluorescein testing demonstrated fluid patency at 22 days post-implantation. Slit lamp and clinical observations showed that VisiPlate was well tolerated, with low levels of conjunctival congestion, conjunctival swelling, aqueous flare, hyphema, and iris involvement from surgery that resolved over time. At sacrifice time points of 93 days and 180 days, the only notable observations were mild levels of conjunctival congestion in implanted eyes. Histopathology showed minimal tissue response and no obvious inflammation, fibrosis, or necrosis around the implant. CONCLUSIONS: The results of this in vivo study demonstrate the biocompatibility and IOP-lowering effect of a multichannel, ultrathin subconjunctival shunt in a rabbit model. The data suggest that VisiPlate may safely enhance aqueous outflow and significantly reduce intraocular pressure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".